Performance Analysis and Bit Allocation of Cell-Free Massive MIMO
Network With Variable-Resolution ADCs
This paper concentrates on cell-free massive multiple-input and
multiple-output (MIMO) network with variable-resolution
analog-to-digital converters (ADCs). In such architecture, all ADCs
equipping at any access point (AP) can use arbitrary bit resolution to
realize adaptive quantization and reduce power consumption. Under this
circumstance, we first introduce a channel estimator based on linear
minimum mean-square error (LMMSE) theory. On this basis, intra-AP and
inter-AP bit allocation problems are investigated to maximize channel
estimation quality subject to the total number of quantization bits. By
leveraging on the statistical properties of the estimated channels and
estimation errors, we then derive the theoretical expressions of the
achievable uplink spectral efficiency (SE) for maximal ratio combining
(MRC) and minimum mean-square error (MMSE) combining, respectively.
Furthermore, to maximize the sum SE under the constraint of total ADC
quantization bits, we also investigate intra-AP and inter-AP bit
allocation problems for both single-user and multi-user scenarios.
Finally, simulation results confirm that our theoretical analyses are
correct and accurate. In addition, we resort to numerical results to
achieve some new insights and verify the advantages and conclusions
pertinent to the proposed bit allocation techniques.